feat(rectification): drive questions from candidate contrast

scripts/rectification/scoring_service.py

@@ -11,7 +11,7 @@ from scripts.active_rectification_event_engine import compute_candidate_static_c
 from scripts.active_rectification_events import CandidateScoreRow
 from scripts.rectification.contracts import LifeEvent, RectificationRequest
 
-ALGORITHM_VERSION = "rectification-v5-matrix-scoring-1"
+ALGORITHM_VERSION = "rectification-v5-matrix-scoring-2"
 INPUT_CONTRACT_VERSION = "rectification-calculation-spec-v4"
 
 
@@ -82,6 +82,42 @@ def _cached_rows(serialized: str) -> tuple[CandidateScoreRow, ...]:
     return tuple(compute_event_candidate_rows(json.loads(serialized)))
 
 
+_RELATIONSHIP_SUPPORT_RULES = (
+    "functional_benefic_auxiliary",
+    "arudha_auxiliary",
+    "ashtakavarga_target_house_support_auxiliary",
+    "shadbala_sthana_drik_naisargika_support_auxiliary",
+    "controlled_transit_jupiter_domain_house",
+)
+_RELATIONSHIP_CHANGE_RULES = (
+    "functional_malefic_auxiliary",
+    "ashtakavarga_target_house_pressure_auxiliary",
+    "shadbala_sthana_drik_naisargika_pressure_auxiliary",
+    "controlled_transit_saturn_domain_house",
+)
+
+
+def _relationship_kind_factor(event_kind: str, rule_ids: Sequence[str]) -> float:
+    if event_kind not in {"relationship_start", "relationship_change"}:
+        return 1.0
+    support = sum(any(rule.endswith(marker) for marker in _RELATIONSHIP_SUPPORT_RULES) for rule in rule_ids)
+    change = sum(any(rule.endswith(marker) for marker in _RELATIONSHIP_CHANGE_RULES) for rule in rule_ids)
+    direction = support - change if event_kind == "relationship_start" else change - support
+    return max(0.8, min(1.2, 1 + 0.08 * direction))
+
+
+def _kind_adjusted_evidence(event: LifeEvent, evidence: dict[str, Any]) -> dict[str, Any]:
+    if event["domain"] != "relationship":
+        return evidence
+    event_kind = event["event_kind"]
+    rules = list(evidence["rule_ids"])
+    return {
+        **evidence,
+        "rule_ids": [*rules, f"event_kind_profile:{event_kind}"],
+        "points": round(float(evidence["points"]) * _relationship_kind_factor(event_kind, rules), 4),
+    }
+
+
 def build_event_contribution_matrix(
     request: RectificationRequest,
     row_provider: Callable[[dict[str, Any]], Sequence[CandidateScoreRow]] | None = None,
@@ -94,7 +130,14 @@ def build_event_contribution_matrix(
     candidate_grid: list[str] | None = None
     for event in request["events"]:
         samples = sample_event_dates(event)
-        sample_rows = [list(provider(_legacy_request(request, event, sampled))) for sampled in samples]
+        sample_rows = []
+        for sampled in samples:
+            rows = list(provider(_legacy_request(request, event, sampled)))
+            sample_rows.append([
+                {**row, "score": adjusted["points"], "evidence": [adjusted]}
+                for row in rows
+                for adjusted in [_kind_adjusted_evidence(event, row["evidence"][0])]
+            ])
         grids = [[row["time"] for row in rows] for rows in sample_rows]
         if any(grid != grids[0] for grid in grids[1:]) or (candidate_grid is not None and grids[0] != candidate_grid):
             raise ValueError("candidate_grid_mismatch")
@@ -109,7 +152,12 @@ def build_event_contribution_matrix(
             matrix[event["id"]][candidate_time] = {
                 "points": round(sum(points) / len(points), 4),
                 "rule_ids": sorted({rule for item in evidences for rule in item["rule_ids"]}),
-                "technique_layers": sorted({rule.split(":", 1)[0] for item in evidences for rule in item["rule_ids"]}),
+                "technique_layers": sorted({
+                    rule.split(":", 1)[0]
+                    for item in evidences
+                    for rule in item["rule_ids"]
+                    if not rule.startswith(("event_kind:", "event_kind_profile:"))
+                }),
             }
         winner = max(set(winners), key=winners.count)
         mean = sum(matrix[event["id"]][time]["points"] for time in candidate_grid) / len(candidate_grid)